Paper
5 May 2006 AKSED: adaptive knowledge-based system for event detection using collaborative unmanned aerial vehicles
Author Affiliations +
Abstract
Advances in sensor technology and image processing have made it possible to equip unmanned aerial vehicles (UAVs) with economical, high-resolution, energy-efficient sensors. Despite the improvements, current UAVs lack autonomous and collaborative operation capabilities, due to limited bandwidth and limited on-board image processing abilities. The situation, however, is changing. In the next generation of UAVs, much image processing can be carried out onboard and communication bandwidth problem will improve. More importantly, with more processing power, collaborative operations among a team of autonomous UAVs can provide more intelligent event detection capabilities. In this paper, we present ideas for developing a system enabling target recognitions by collaborative operations of autonomous UAVs. UAVs are configured in three stages: manufacturing, mission planning, and deployment. Different sets of information are needed at different stages, and the resulting outcome is an optimized event detection code deployed onto a UAV. The envisioned system architecture and the contemplated methodology, together with problems to be addressed, are presented.
© (2006) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
X. Sean Wang, Byung Suk Lee, and Firooz Sadjadi "AKSED: adaptive knowledge-based system for event detection using collaborative unmanned aerial vehicles", Proc. SPIE 6234, Automatic Target Recognition XVI, 62340Q (5 May 2006); https://doi.org/10.1117/12.667844
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KEYWORDS
Unmanned aerial vehicles

Sensors

Image processing

Infrared sensors

Image sensors

Visualization

Manufacturing

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